基于马尔可夫博弈模型的网络安全态势感知方法

Bingjie Lin, Jie Cheng, Jiahui Wei, Ang Xia
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引用次数: 0

摘要

网络安全态势感知(NSS)已成为一个热点问题。本文首先阐述了马尔可夫模型的基本原理,然后给出了应用马尔可夫博弈模型的充分必要条件。最后,以模糊综合评价模型为理论基础,从网络随机性、非合作性和动态演化等方面分析了马尔可夫博弈模型下NSS感知方法的应用领域。评价结果表明,基于马尔可夫博弈模型的NSS感知方法最适合金融领域,其次是教育领域。此外,该模型还可用于不同行业网络安全状况感知方法的适用性评价。当然,在不同的类别下,在不同的网络安全状况感知方法的前提下,各种影响因素的比例是不同的,一旦比例不合理,就会造成计算过程的错误,从而影响结果。
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A Sensing Method of Network Security Situation Based on Markov Game Model
The sensing of network security situation (NSS) has become a hot issue. This paper first describes the basic principle of Markov model and then the necessary and sufficient conditions for the application of Markov game model. And finally, taking fuzzy comprehensive evaluation model as the theoretical basis, this paper analyzes the application fields of the sensing method of NSS with Markov game model from the aspects of network randomness, non-cooperative and dynamic evolution. Evaluation results show that the sensing method of NSS with Markov game model is best for financial field, followed by educational field. In addition, the model can also be used in the applicability evaluation of the sensing methods of different industries’ network security situation. Certainly, in different categories, and under the premise of different sensing methods of network security situation, the proportions of various influencing factors are different, and once the proportion is unreasonable, it will cause false calculation process and thus affect the results.
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来源期刊
International Journal of Circuits, Systems and Signal Processing
International Journal of Circuits, Systems and Signal Processing Engineering-Electrical and Electronic Engineering
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